The role of the clinician in the multi-omics era: are you ready?

An integrated multi-omics approach allowed ultra-rapid diagnosis of a deep intronic pathogenic variant in PDHX and precision treatment in a neonate critically ill with lactic acidosis

The diagnosis of mitochondrial disorders is complex. Rapid whole genome sequencing is a first line test for critically ill neonates and infants allowing rapid diagnosis and treatment. Standard genomic technology and bioinformatic pipelines still have an incomplete diagnostic yield requiring complementary approaches. There are currently limited options for rapid additional tests to continue a diagnostic work-up after a negative rapid whole-genome sequencing result, reflecting a gap in clinical practice. Multi-modal integrative diagnostic approaches derived from systems biology including proteomics and transcriptomics show promise in suspected mitochondrial disorders. In this article, we report the case of a neonate who presented with severe lactic acidosis on the second day of life, for whom an initial report of ultra-rapid genome sequencing was negative. The patient was started on dichloroacetate as an emergency investigational new drug (eIND), with a sharp decline in lactic acid levels and clinical stabilization. A proteomics-based approach identified a complete absence of PDHX protein, leading to a re-review of the genome data for the PDHX gene in which a homozygous deep intronic pathogenic variant was identified. Subsequent testing in the following months confirmed the diagnosis with deficient pyruvate dehydrogenase enzyme activity, reduced protein levels of E3-binding protein, and confirmed by mRNA sequencing to lead to the inclusion of a cryptic exon and a premature stop codon. This case highlights the power of rapid proteomics in guiding genomic analysis. It also shows a promising role for dichloroacetate treatment in controlling lactic acidosis related to PDHX-related pyruvate dehydrogenase complex deficiency.

Amino Acid Profile Alterations in Phenylketonuria: Implications for Clinical Practice

Patients with phenylketonuria (PKU) must restrict their intake of phenylalanine, which can also affect the levels of other essential and non-essential amino acids due to inadequate supply. Therefore, our objective was to assess amino acids in serum samples from 20 PKU patients and compare them with results from 51 healthy subjects. A sample analysis was conducted using liquid chromatography-tandem mass spectrometry. We obtained levels of 28 substances, including amino acids, biogenic amines, carnitine, and acetylcarnitine. Kynurenine (p = 0.000001), tyrosine (p = 0.0002), asparagine (p = 0.001), proline (p = 0.012), and the kynurenine/tryptophan ratio (p < 0.000001) were identified as features that differed between the studied groups, being significantly lower in patients with PKU. Glycine (p = 0.000012), putrescine (p = 0.0055), asymmetric dimethylarginine (p = 0.01), creatinine (p = 0.035) levels, as well as the total level of glucogenic amino acids (p = 0.0018), and the ratios of putrescine/ornithine (p = 0.003) and citrulline/ornithine (p = 0.0043) were significantly higher in the PKU group. In conclusion, the amino acid profiles in patients with PKU differ significantly from those in healthy peers, with potential clinical implications. These findings confirm the importance of metabolic testing in clinical practice and highlight the necessity for adequate dietary monitoring and adjustment.

Personalized nutrition: the end of the one-diet-fits-all era

Personalized Nutrition emerged as a new trend for providing nutritional and food advice based on the individual's genetic composition, a field driven by the advancements in the multi-omic sciences throughout the last century. It intends not only to tailor the recommended daily allowances of nutrients and functional foods that a person may need but also to maintain the principles of sustainability and eco-friendliness. This principle implies the implementation of strategies within the healthcare system to advocate for the ending of the one-diet-fits-all paradigm by considering a personalized diet as an ally to prevent diet-related chronic diseases. In this Perspective, we highlight the potential benefits of such a paradigm within the region of Latin America, particularly Mexico, where the genetic admixture of the population, food biodiversity, and food culture provide unique opportunities to establish personalized nutrigenetic strategies. These strategies could play a crucial role in preventing chronic diseases and addressing the challenges confronted in the region.

Next-generation sequencing and bioinformatics in rare movement disorders

The ability to sequence entire exomes and genomes has revolutionized molecular testing in rare movement disorders, and genomic sequencing is becoming an integral part of routine diagnostic workflows for these heterogeneous conditions. However, interpretation of the extensive genomic variant information that is being generated presents substantial challenges. In this Perspective, we outline multidimensional strategies for genetic diagnosis in patients with rare movement disorders. We examine bioinformatics tools and computational metrics that have been developed to facilitate accurate prioritization of disease-causing variants. Additionally, we highlight community-driven data-sharing and case-matchmaking platforms, which are designed to foster the discovery of new genotype-phenotype relationships. Finally, we consider how multiomic data integration might optimize diagnostic success by combining genomic, epigenetic, transcriptomic and/or proteomic profiling to enable a more holistic evaluation of variant effects. Together, the approaches that we discuss offer pathways to the improved understanding of the genetic basis of rare movement disorders.

Incorporating functional genomics into the pathology-supported genetic testing framework implemented in South Africa: A future view of precision medicine for breast carcinomas

A pathology-supported genetic testing (PSGT) framework was established in South Africa to improve access to precision medicine for patients with breast carcinomas. Nevertheless, the frequent identification of variants of uncertain significance (VUSs) with the use of genome-scale next-generation sequencing has created a bottleneck in the return of results to patients. This review highlights the importance of incorporating functional genomics into the PSGT framework as a proposed initiative. Here, we explore various model systems and experimental methods available for conducting functional studies in South Africa to enhance both variant classification and clinical interpretation. We emphasize the distinct advantages of using in vitro, in vivo, and translational ex vivo models to improve the effectiveness of precision oncology. Moreover, we highlight the relevance of methodologies such as protein modelling and structural bioinformatics, multi-omics, metabolic activity assays, flow cytometry, cell migration and invasion assays, tube-formation assays, multiplex assays of variant effect, and database mining and machine learning models. The selection of the appropriate experimental approach largely depends on the molecular mechanism of the gene under investigation and the predicted functional effect of the VUS. However, before making final decisions regarding the pathogenicity of VUSs, it is essential to assess the functional evidence and clinical outcomes under current variant interpretation guidelines. The inclusion of a functional genomics infrastructure within the PSGT framework will significantly advance the reclassification of VUSs and enhance the precision medicine pipeline for patients with breast carcinomas in South Africa.

Integrative omics approaches to advance rare disease diagnostics

Over the past decade high-throughput DNA sequencing approaches, namely whole exome and whole genome sequencing became a standard procedure in Mendelian disease diagnostics. Implementation of these technologies greatly facilitated diagnostics and shifted the analysis paradigm from variant identification to prioritisation and evaluation. The diagnostic rates vary widely depending on the cohort size, heterogeneity and disease and range from around 30% to 50% leaving the majority of patients undiagnosed. Advances in omics technologies and computational analysis provide an opportunity to increase these unfavourable rates by providing evidence for disease-causing variant validation and prioritisation. This review aims to provide an overview of the current application of several omics technologies including RNA-sequencing, proteomics, metabolomics and DNA-methylation profiling for diagnostics of rare genetic diseases in general and inborn errors of metabolism in particular.

Inherited metabolic disorders in adults: systematic review on patient characteristics and diagnostic yield of broad sequencing techniques (exome and genome sequencing)

BACKGROUND/OBJECTIVES

The timely diagnosis of inherited metabolic disorders (IMD) is essential for initiating treatment, prognostication and genetic testing of relatives. Recognition of IMD in adults is difficult, because phenotypes are different from those in children and influenced by symptoms from acquired conditions. This systematic literature review aims to answer the following questions: (1) What is the diagnostic yield of exome/genome sequencing (ES/GS) for IMD in adults with unsolved phenotypes? (2) What characteristics do adult patients diagnosed with IMD through ES/GS have?

METHODS

A systematic search was conducted using the following search terms (simplified): "Whole exome sequencing (WES)," "Whole genome sequencing (WGS)," "IMD," "diagnostics" and the 1,450 known metabolic genes derived from ICIMD. Data from 695 articles, including 27,702 patients, were analyzed using two different methods. First, the diagnostic yield for IMD in patients presenting with a similar phenotype was calculated. Secondly, the characteristics of patients diagnosed with IMD through ES/GS in adulthood were established.

RESULTS

The diagnostic yield of ES and/or GS for adult patients presenting with unexplained neurological symptoms is 11% and for those presenting with dyslipidemia, diabetes, auditory and cardiovascular symptoms 10, 9, 8 and 7%, respectively. IMD patients diagnosed in adulthood (n = 1,426), most frequently portray neurological symptoms (65%), specifically extrapyramidal/cerebellar symptoms (57%), intellectual disability/dementia/psychiatric symptoms (41%), pyramidal tract symptoms/myelopathy (37%), peripheral neuropathy (18%), and epileptic seizures (16%). The second most frequently observed symptoms were ophthalmological (21%). In 47% of the IMD diagnosed patients, symptoms from multiple organ systems were reported. On average, adult patients are diagnosed 15 years after first presenting symptoms. Disease-related abnormalities in metabolites in plasma, urine or cerebral spinal fluid were identified in 40% of all patients whom underwent metabolic screening. In 52% the diagnosis led to identification of affected family members with the same IMD.

CONCLUSION

ES and/or GS is likely to yield an IMD diagnosis in adult patients presenting with an unexplained neurological phenotype, as well as in patients with a phenotype involving multiple organ systems. If a gene panel does not yield a conclusive diagnosis, it is worthwhile to analyze all known disease genes. Further prospective research is needed to establish the best diagnostic approach (type and sequence of metabolic and genetic test) in adult patients presenting with a wide range of symptoms, suspected of having an IMD.

SYSTEMATIC REVIEW REGISTRATION

https://www.crd.york.ac.uk/prospero/, identifier: CRD42021295156.

Statistical analysis of high-dimensional biomedical data: a gentle introduction to analytical goals, common approaches and challenges

BACKGROUND

In high-dimensional data (HDD) settings, the number of variables associated with each observation is very large. Prominent examples of HDD in biomedical research include omics data with a large number of variables such as many measurements across the genome, proteome, or metabolome, as well as electronic health records data that have large numbers of variables recorded for each patient. The statistical analysis of such data requires knowledge and experience, sometimes of complex methods adapted to the respective research questions.

METHODS

Advances in statistical methodology and machine learning methods offer new opportunities for innovative analyses of HDD, but at the same time require a deeper understanding of some fundamental statistical concepts. Topic group TG9 "High-dimensional data" of the STRATOS (STRengthening Analytical Thinking for Observational Studies) initiative provides guidance for the analysis of observational studies, addressing particular statistical challenges and opportunities for the analysis of studies involving HDD. In this overview, we discuss key aspects of HDD analysis to provide a gentle introduction for non-statisticians and for classically trained statisticians with little experience specific to HDD.

RESULTS

The paper is organized with respect to subtopics that are most relevant for the analysis of HDD, in particular initial data analysis, exploratory data analysis, multiple testing, and prediction. For each subtopic, main analytical goals in HDD settings are outlined. For each of these goals, basic explanations for some commonly used analysis methods are provided. Situations are identified where traditional statistical methods cannot, or should not, be used in the HDD setting, or where adequate analytic tools are still lacking. Many key references are provided.

CONCLUSIONS

This review aims to provide a solid statistical foundation for researchers, including statisticians and non-statisticians, who are new to research with HDD or simply want to better evaluate and understand the results of HDD analyses.

Influence of bacterial and alveolar cell co-culture on microbial VOC production using HS-GC/MS

Volatile organic compounds (VOCs) found in exhaled breath continue to garner interest as an alternative diagnostic tool in pulmonary infections yet, their clinical integration remains a challenge with difficulties in translating identified biomarkers. Alterations in bacterial metabolism secondary to host nutritional availability may explain this but is often inadequately modelled in vitro. The influence of more clinically relevant nutrients on VOC production for two common respiratory pathogens was investigated. VOCs from Staphylococcus aureus (S.aureus) and Pseudomonas aeruginosa (P.aeruginosa) cultured with and without human alveolar A549 epithelial cells were analyzed using headspace extraction coupled with gas chromatography-mass spectrometry. Untargeted and targeted analyses were performed, volatile molecules identified from published data, and the differences in VOC production evaluated. Principal component analysis (PCA) could differentiate alveolar cells from either S. aureus or P. aeruginosa when cultured in isolation based on PC1 (p = 0.0017 and 0.0498, respectively). However, this separation was lost for S. aureus (p = 0.31) but not for P. aeruginosa (p = 0.028) when they were cultured with alveolar cells. S. aureus cultured with alveolar cells led to higher concentrations of two candidate biomarkers, 3-methyl-1-butanol (p = 0.001) and 3-methylbutanal (p = 0.002) when compared to S. aureus, alone. P. aeruginosa metabolism resulted in less generation of pathogen-associated VOCs when co-cultured with alveolar cells compared to culturing in isolation. VOC biomarkers previously considered indicative of bacterial presence are influenced by the local nutritional environment and this should be considered when evaluating their biochemical origin.

The Autism Spectrum: Behavioral, Psychiatric and Genetic Associations

Autism spectrum disorder (ASD) consists of a group of heterogeneous genetic neurobehavioral disorders associated with developmental impairments in social communication skills and stereotypic, rigid or repetitive behaviors. We review common behavioral, psychiatric and genetic associations related to ASD. Autism affects about 2% of children with 4:1 male-to-female ratio and a heritability estimate between 70 and 90%. The etiology of ASD involves a complex interplay between inheritance and environmental factors influenced by epigenetics. Over 800 genes and dozens of genetic syndromes are associated with ASD. Novel gene–protein interactions with pathway and molecular function analyses have identified at least three functional pathways including chromatin modeling, Wnt, Notch and other signaling pathways and metabolic disturbances involving neuronal growth and dendritic spine profiles. An estimated 50% of individuals with ASD are diagnosed with chromosome deletions or duplications (e.g., 15q11.2, BP1-BP2, 16p11.2 and 15q13.3), identified syndromes (e.g., Williams, Phelan-McDermid and Shprintzen velocardiofacial) or single gene disorders. Behavioral and psychiatric conditions in autism impacted by genetics influence clinical evaluations, counseling, diagnoses, therapeutic interventions and treatment approaches. Pharmacogenetics testing is now possible to help guide the selection of psychotropic medications to treat challenging behaviors or co-occurring psychiatric conditions commonly seen in ASD. In this review of the autism spectrum disorder, behavioral, psychiatric and genetic observations and associations relevant to the evaluation and treatment of individuals with ASD are discussed.

Lipidomics-Paving the Road towards Better Insight and Precision Medicine in Rare Metabolic Diseases

Even though the application of Next-Generation Sequencing (NGS) has significantly facilitated the identification of disease-associated mutations, the diagnostic rate of rare diseases is still below 50%. This causes a diagnostic odyssey and prevents specific treatment, as well as genetic counseling for further family planning. Increasing the diagnostic rate and reducing the time to diagnosis in children with unclear disease are crucial for a better patient outcome and improvement of quality of life. In many cases, NGS reveals variants of unknown significance (VUS) that need further investigations. The delineation of novel (lipid) biomarkers is not only crucial to prove the pathogenicity of VUS, but provides surrogate parameters for the monitoring of disease progression and therapeutic interventions. Lipids are essential organic compounds in living organisms, serving as building blocks for cellular membranes, energy storage and signaling molecules. Among other disorders, an imbalance in lipid homeostasis can lead to chronic inflammation, vascular dysfunction and neurodegenerative diseases. Therefore, analyzing lipids in biological samples provides great insight into the underlying functional role of lipids in healthy and disease statuses. The method of choice for lipid analysis and/or huge assemblies of lipids (=lipidome) is mass spectrometry due to its high sensitivity and specificity. Due to the inherent chemical complexity of the lipidome and the consequent challenges associated with analyzing it, progress in the field of lipidomics has lagged behind other omics disciplines. However, compared to the previous decade, the output of publications on lipidomics has increased more than 17-fold within the last decade and has, therefore, become one of the fastest-growing research fields. Combining multiple omics approaches will provide a unique and efficient tool for determining pathogenicity of VUS at the functional level, and thereby identifying rare, as well as novel, genetic disorders by molecular techniques and biochemical analyses.

Endotoxin in Sepsis: Methods for LPS Detection and the Use of Omics Techniques

Lipopolysaccharide (LPS) or endotoxin, the major cell wall component of Gram-negative bacteria, plays a pivotal role in the pathogenesis of sepsis. It is able to activate the host defense system through interaction with Toll-like receptor 4, thus triggering pro-inflammatory mechanisms. A large amount of LPS induces inappropriate activation of the immune system, triggering an exaggerated inflammatory response and consequent extensive organ injury, providing the basis of sepsis damage. In this review, we will briefly describe endotoxin's molecular structure and its main pathogenetic action during sepsis. In addition, we will summarize the main different available methods for endotoxin detection with a special focus on the wider spectrum offered by omics technologies (genomics, transcriptomics, proteomics, and metabolomics) and promising applications of these in the identification of specific biomarkers for sepsis.

An integrated multiomic approach as an excellent tool for the diagnosis of metabolic diseases: our first 3720 patients

To present our experience using a multiomic approach, which integrates genetic and biochemical testing as a first-line diagnostic tool for patients with inherited metabolic disorders (IMDs). A cohort of 3720 patients from 62 countries was tested using a panel including 206 genes with single nucleotide and copy number variant (SNV/CNV) detection, followed by semi-automatic variant filtering and reflex biochemical testing (25 assays). In 1389 patients (37%), a genetic diagnosis was achieved. Within this cohort, the highest diagnostic yield was obtained for patients from Asia (57.5%, mainly from Pakistan). Overall, 701 pathogenic/likely pathogenic unique SNVs and 40 CNVs were identified. In 620 patients, the result of the biochemical tests guided variant classification and reporting. Top five diagnosed diseases were: Gaucher disease, Niemann-Pick disease type A/B, phenylketonuria, mucopolysaccharidosis type I, and Wilson disease. We show that integrated genetic and biochemical testing facilitated the decision on clinical relevance of the variants and led to a high diagnostic yield (37%), which is comparable to exome/genome sequencing. More importantly, up to 43% of these patients (n = 610) could benefit from medical treatments (e.g., enzyme replacement therapy). This multiomic approach constitutes a unique and highly effective tool for the genetic diagnosis of IMDs.

Recent Progress and Future Direction for the Application of Multiomics Data in Clinical Liver Transplantation

Omics data address key issues in liver transplantation (LT) as the most effective therapeutic means for end-stage liver disease. The purpose of this study was to review the current application and future direction for omics in LT. We reviewed the use of multiomics to elucidate the pathogenesis leading to LT and prognostication. Future directions with respect to the use of omics in LT are also described based on perspectives of surgeons with experience in omics. Significant molecules were identified and summarized based on omics, with a focus on post-transplant liver fibrosis, early allograft dysfunction, tumor recurrence, and graft failure. We emphasized the importance omics for clinicians who perform LTs and prioritized the directions that should be established. We also outlined the ideal workflow for omics in LT. In step with advances in technology, the quality of omics data can be guaranteed using an improved algorithm at a lower price. Concerns should be addressed on the translational value of omics for better therapeutic effects in patients undergoing LT.

Breast cancer in the era of integrating “Omics” approaches

Worldwide, breast cancer is the leading cause of cancer-related deaths in women. Breast cancer is a heterogeneous disease characterized by different clinical outcomes in terms of pathological features, response to therapies, and long-term patient survival. Thus, the heterogeneity found in this cancer led to the concept that breast cancer is not a single disease, being very heterogeneous both at the molecular and clinical level, and rather represents a group of distinct neoplastic diseases of the breast and its cells. Indubitably, in the past decades we witnessed a significant development of innovative therapeutic approaches, including targeted and immunotherapies, leading to impressive results in terms of increased survival for breast cancer patients. However, these multimodal treatments fail to prevent recurrence and metastasis. Therefore, it is urgent to improve our understanding of breast tumor and metastasis biology. Over the past few years, high-throughput “omics” technologies through the identification of novel biomarkers and molecular profiling have shown their great potential in generating new insights in the study of breast cancer, also improving diagnosis, prognosis and prediction of response to treatment. In this review, we discuss how the implementation of “omics” strategies and their integration may lead to a better comprehension of the mechanisms underlying breast cancer. In particular, with the aim to investigate the correlation between different “omics” datasets and to define the new important key pathway and upstream regulators in breast cancer, we applied a new integrative meta-analysis method to combine the results obtained from genomics, proteomics and metabolomics approaches in different revised studies.

Personalized medicine for rare neurogenetic disorders: can we make it happen?

Rare neurogenetic disorders are collectively common, affecting 3% of the population, and often manifest with complex multiorgan comorbidity. With advances in genetic, -omics, and computational analysis, more children can be diagnosed and at an earlier age. Innovations in translational research facilitate the identification of treatment targets and development of disease-modifying drugs such as gene therapy, nutraceuticals, and drug repurposing. This increasingly allows targeted therapy to prevent the often devastating manifestations of rare neurogenetic disorders. In this perspective, successes in diagnosis, prevention, and treatment are discussed with a focus on inherited disorders of metabolism. Barriers for the identification, development, and implementation of rare disease-specific therapies are discussed. New methodologies, care networks, and collaborative frameworks are proposed to optimize the potential of personalized genomic medicine to decrease morbidity and improve lives of these vulnerable patients.

Indoor Air Pollution Increases the Risk of Lung Cancer

(1) Background: Cooking and burning incense are important sources of indoor air pollutants. No studies have provided biological evidence of air pollutants in the lungs to support this association. Analysis of pleural fluid may be used to measure the internal exposure dose of air pollutants in the lung. The objective of this study was to provide biological evidence of indoor air pollutants and estimate their risk of lung cancer. (2) Methods: We analyzed 14 common air pollutants in the pleural fluid of 39 cases of lung adenocarcinoma and 40 nonmalignant controls by gas chromatography-mass spectrometry. (3) Results: When we excluded the current smokers and adjusted for age, the adjusted odds ratios (ORs) were 2.22 (95% confidence interval CI = 0.77-6.44) for habitual cooking at home and 3.05 (95% CI = 1.06-8.84) for indoor incense burning. In females, the adjusted ORs were 5.39 (95% CI = 1.11-26.20) for habitual cooking at home and 6.01 (95% CI = 1.14-31.66) for indoor incense burning. In pleural fluid, the most important exposure biomarkers for lung cancer were naphthalene, ethylbenzene, and o-xylene. (4) Conclusions: Habitual cooking and indoor incense burning increased the risk of lung adenocarcinoma.

Knowledge gaps in late-onset neonatal sepsis in preterm neonates: a roadmap for future research

Late-onset neonatal sepsis (LONS) remains an important threat to the health of preterm neonates in the neonatal intensive care unit. Strategies to optimize care for preterm neonates with LONS are likely to improve survival and long-term neurocognitive outcomes. However, many important questions on how to improve the prevention, early detection, and therapy for LONS in preterm neonates remain unanswered. This review identifies important knowledge gaps in the management of LONS and describe possible methods and technologies that can be used to resolve these knowledge gaps. The availability of computational medicine and hypothesis-free-omics approaches give way to building bedside feedback tools to guide clinicians in personalized management of LONS. Despite advances in technology, implementation in clinical practice is largely lacking although such tools would help clinicians to optimize many aspects of the management of LONS. We outline which steps are needed to get possible research findings implemented on the neonatal intensive care unit and provide a roadmap for future research initiatives. IMPACT: This review identifies knowledge gaps in prevention, early detection, antibiotic, and additional therapy of late-onset neonatal sepsis in preterm neonates and provides a roadmap for future research efforts. Research opportunities are addressed, which could provide the means to fill knowledge gaps and the steps that need to be made before possible clinical use. Methods to personalize medicine and technologies feasible for bedside clinical use are described.

Primary lymphoedema

Lymphoedema is the swelling of one or several parts of the body owing to lymph accumulation in the extracellular space. It is often chronic, worsens if untreated, predisposes to infections and causes an important reduction in quality of life. Primary lymphoedema (PLE) is thought to result from abnormal development and/or functioning of the lymphatic system, can present in isolation or as part of a syndrome, and can be present at birth or develop later in life. Mutations in numerous genes involved in the initial formation of lymphatic vessels (including valves) as well as in the growth and expansion of the lymphatic system and associated pathways have been identified in syndromic and non-syndromic forms of PLE. Thus, the current hypothesis is that most cases of PLE have a genetic origin, although a causative mutation is identified in only about one-third of affected individuals. Diagnosis relies on clinical presentation, imaging of the structure and functionality of the lymphatics, and in genetic analyses. Management aims at reducing or preventing swelling by compression therapy (with manual drainage, exercise and compressive garments) and, in carefully selected cases, by various surgical techniques. Individuals with PLE often have a reduced quality of life owing to the psychosocial and lifelong management burden associated with their chronic condition. Improved understanding of the underlying genetic origins of PLE will translate into more accurate diagnosis and prognosis and personalized treatment.

Analytical Evaluation of the Ideal Strategy for High-Throughput Flow Injection Analysis by Tandem Mass Spectrometry in Routine Newborn Screening

The introduction of tandem mass spectrometry (MS/MS) to clinical laboratories and the advent of expanded newborn screening (NBS) were crucial changes to public health programs worldwide. Speed, robustness, accuracy, selectivity, and specificity of analysis are all requirements of expanded NBS and are needed to minimize false positive results risks, to possibly eliminate false negatives, and to improve the positive predictive value of NBS. In this study, we firstly evaluated the analytical performances of the RenataDX Screening System, a fully integrated flow-injection MS/MS (FIA-MS/MS) IVD system for high-throughput dried blood spot (DBS) analysis in a routine NBS laboratory. Since a choice of several commercial NBS kits is available, we sought to compare NeoBase^TM 2 (PerkinElmer^®) and MassChrom^® (Chromsystems) non-derivatized kits on the RenataDX platform by evaluating their analytical performances. Moreover, we verified the degree of correlation between data obtained by the two different NBS MS/MS kits by FIA-MS/MS of over 500 samples. Our data suggest that both methods correlate well with clinically insignificant differences that do not impact the NBS result. Finally, while NeoBase™ 2 offers an easier and faster sample preparation, MassChrom^® provides a cleaner sample extract which empirically should improve instrument reliability.

Undisclosed, unmet and neglected challenges in multi-omics studies

Multi-omics approaches have become a reality in both large genomics projects and small laboratories. However, the multi-omics research community still faces a number of issues that have either not been sufficiently discussed or for which current solutions are still limited. In this Perspective, we elaborate on these limitations and suggest points of attention for future research. We finally discuss new opportunities and challenges brought to the field by the rapid development of single-cell high-throughput molecular technologies.

Translational Applications of Artificial Intelligence and Machine Learning for Diagnostic Pathology in Lymphoid Neoplasms: A Comprehensive and Evolutive Analysis

Genomic analysis and digitalization of medical records have led to a big data scenario within hematopathology. Artificial intelligence and machine learning tools are increasingly used to integrate clinical, histopathological, and genomic data in lymphoid neoplasms. In this study, we identified global trends, cognitive, and social framework of this field from 1990 to 2020. Metadata were obtained from the Clarivate Analytics Web of Science database in January 2021. A total of 525 documents were assessed by document type, research areas, source titles, organizations, and countries. SciMAT and VOSviewer package were used to perform scientific mapping analysis. Geographical distribution showed the USA and People's Republic of China as the most productive countries, reporting up to 190 (36.19%) of all documents. A third-degree polynomic equation predicts that future global production in this area will be three-fold the current number, near 2031. Thematically, current research is focused on the integration of digital image analysis and genomic sequencing in Non-Hodgkin lymphomas, prediction of chemotherapy response and validation of new prognostic models. These findings can serve pathology departments to depict future clinical and research avenues, but also, public institutions and administrations to promote synergies and optimize funding allocation.

Treatable inherited metabolic disorders causing intellectual disability: 2021 review and digital app

BACKGROUND

The Treatable ID App was created in 2012 as digital tool to improve early recognition and intervention for treatable inherited metabolic disorders (IMDs) presenting with global developmental delay and intellectual disability (collectively 'treatable IDs'). Our aim is to update the 2012 review on treatable IDs and App to capture the advances made in the identification of new IMDs along with increased pathophysiological insights catalyzing therapeutic development and implementation.

METHODS

Two independent reviewers queried PubMed, OMIM and Orphanet databases to reassess all previously included disorders and therapies and to identify all reports on Treatable IDs published between 2012 and 2021. These were included if listed in the International Classification of IMDs (ICIMD) and presenting with ID as a major feature, and if published evidence for a therapeutic intervention improving ID primary and/or secondary outcomes is available. Data on clinical symptoms, diagnostic testing, treatment strategies, effects on outcomes, and evidence levels were extracted and evaluated by the reviewers and external experts. The generated knowledge was translated into a diagnostic algorithm and updated version of the App with novel features.

RESULTS

Our review identified 116 treatable IDs (139 genes), of which 44 newly identified, belonging to 17 ICIMD categories. The most frequent therapeutic interventions were nutritional, pharmacological and vitamin and trace element supplementation. Evidence level varied from 1 to 3 (trials, cohort studies, case-control studies) for 19% and 4-5 (case-report, expert opinion) for 81% of treatments. Reported effects included improvement of clinical deterioration in 62%, neurological manifestations in 47% and development in 37%.

CONCLUSION

The number of treatable IDs identified by our literature review increased by more than one-third in eight years. Although there has been much attention to gene-based and enzyme replacement therapy, the majority of effective treatments are nutritional, which are relatively affordable, widely available and (often) surprisingly effective. We present a diagnostic algorithm (adjustable to local resources and expertise) and the updated App to facilitate a swift and accurate workup, prioritizing treatable IDs. Our digital tool is freely available as Native and Web App (www.treatable-id.org) with several novel features. Our Treatable ID endeavor contributes to the Treatabolome and International Rare Diseases Research Consortium goals, enabling clinicians to deliver rapid evidence-based interventions to our rare disease patients.

The progressive intellectual and neurological deterioration study: a game changer

This commentary is on the original article by Verity et al. on pages 287–294 of this issue.

The role of clinical response to treatment in determining pathogenicity of genomic variants

PURPOSE

The 2015 American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) guidelines for the interpretation of sequence variants provide a framework to standardize terminology in the classification of variants uncovered through genetic testing. We aimed to assess the validity of utilizing clinical response to therapies specifically targeted to a suspected disease in clarifying variant pathogenicity.

METHODS

Five families with disparate clinical presentations and different genetic diseases evaluated and treated in multiple diagnostic settings are summarized.

RESULTS

Extended evaluations indicated possible genetic diagnoses and assigned candidate causal variants, but the cumulative clinical, biochemical, and molecular information in each instance was not completely consistent with the identified disease. Initiation of treatment specific to the suspected diagnoses in the affected individuals led to clinical improvement in all five families.

CONCLUSION

We propose that the effect of therapies that are specific and targeted to treatable genetic diseases embodies an in vivo physiological response and could be considered as additional criteria within the 2015 ACMG/AMP guidelines in determining genomic variant pathogenicity.

Clinical Validation of Targeted and Untargeted Metabolomics Testing for Genetic Disorders: A 3 Year Comparative Study

Global untargeted metabolomics (GUM) has entered clinical diagnostics for genetic disorders. We compared the clinical utility of GUM with traditional targeted metabolomics (TM) as a screening tool in patients with established genetic disorders and determined the scope of GUM as a discovery tool in patients with no diagnosis under investigation. We compared TM and GUM data in 226 patients. The first cohort (n = 87) included patients with confirmed inborn errors of metabolism (IEM) and genetic syndromes; the second cohort (n = 139) included patients without diagnosis who were undergoing evaluation for a genetic disorder. In patients with known disorders (n = 87), GUM performed with a sensitivity of 86% (95% CI: 78–91) compared with TM for the detection of 51 diagnostic metabolites. The diagnostic yield of GUM in patients under evaluation with no established diagnosis (n = 139) was 0.7%. GUM successfully detected the majority of diagnostic compounds associated with known IEMs. The diagnostic yield of both targeted and untargeted metabolomics studies is low when assessing patients with non-specific, neurological phenotypes. GUM shows promise as a validation tool for variants of unknown significance in candidate genes in patients with non-specific phenotypes.

Advances in the diagnosis of inherited neuromuscular diseases and implications for therapy development

Advances in DNA sequencing technologies have resulted in a near doubling, in under 10 years, of the number of causal genes identified for inherited neuromuscular disorders. However, around half of patients, whether children or adults, do not receive a molecular diagnosis after initial diagnostic workup. Massively parallel technologies targeting RNA, proteins, and metabolites are being increasingly used to diagnose these unsolved cases. The use of these technologies to delineate pathways, biomarkers, and therapeutic targets has led to new approaches entering the drug development pipeline. However, these technologies might give rise to misleading conclusions if used in isolation, and traditional techniques including comprehensive neurological evaluation, histopathology, and biochemistry continue to have a crucial role in diagnostics. For optimal diagnosis, prognosis, and precision medicine, no single ruling technology exists. Instead, an interdisciplinary approach combining novel and traditional neurological techniques with computer-aided analysis and international data sharing is needed to advance the diagnosis and treatment of neuromuscular disorders.

Participatory Genomic Testing Can Effectively Disseminate Cardiovascular Pharmacogenomics Concepts within Federally Qualified Health Centers: A Feasibility Study

Objective

We assessed feasibility of an educational program designed to enhance stakeholder knowledge and perceptions of pharmacogenomics at a federally qualified health center (FQHC).

Design

FQHCs have a rich history of providing care to the underserved, but often are not represented by studies evaluating cutting-edge concepts. We used a novel educational platform to provide participatory genomic testing and classroom education. We assessed participant knowledge and perceptions using questionnaires between May and July 2018.

Setting

We partnered with a FQHC affiliated with an academic medical center in Chicago.

Participants

Using convenience sampling, we recruited 20 providers and 10 community members for a feasibility study. Providers included physicians, physician extenders, community health workers, and patient health navigators. Community members were patients, supporters, and/or FQHC advisory board members.

Intervention

Participants had the option to undergo personal genomic testing. Online educational modules included basic genetics, cardiovascular pharmacogenomics, and personalized medicine. Education concluded in a 2-hour live course with case-based discussions.

Main Outcome Measures

Our main outcome was testing pilot feasibility. Baseline knowledge and perceptions were compared with post-intervention assessments using descriptive statistics, t tests (or Wilcoxon rank-sum) for continuous variables and chi-squared (or Fisher's exact) for categorical variables.

Results

We found that attitudes toward the intervention were positive and remained so after intervention. Our intervention was both feasible and acceptable. Genomics knowledge increased for nearly all participants.

Conclusions

We have determined that a pharmacogenomics educational program tailored for an underrepresented community is feasible and acceptable. Outcomes will advise methodology for larger implementation studies.

Combining clinical and molecular data in regression prediction models: insights from a simulation study

Data integration, i.e. the use of different sources of information for data analysis, is becoming one of the most important topics in modern statistics. Especially in, but not limited to, biomedical applications, a relevant issue is the combination of low-dimensional (e.g. clinical data) and high-dimensional (e.g. molecular data such as gene expressions) data sources in a prediction model. Not only the different characteristics of the data, but also the complex correlation structure within and between the two data sources, pose challenging issues. In this paper, we investigate these issues via simulations, providing some useful insight into strategies to combine low- and high-dimensional data in a regression prediction model. In particular, we focus on the effect of the correlation structure on the results, while accounting for the influence of our specific choices in the design of the simulation study.

What Is Karyotype Coding and Why Is Genomic Topology Important for Cancer and Evolution?

While the importance of chromosomal/nuclear variations vs. gene mutations in diseases is becoming more appreciated, less is known about its genomic basis. Traditionally, chromosomes are considered the carriers of genes, and genes define bio-inheritance. In recent years, the gene-centric concept has been challenged by the surprising data of various sequencing projects. The genome system theory has been introduced to offer an alternative framework. One of the key concepts of the genome system theory is karyotype or chromosomal coding: chromosome sets function as gene organizers, and the genomic topologies provide a context for regulating gene expression and function. In other words, the interaction of individual genes, defined by genomic topology, is part of the full informational system. The genes define the “parts inheritance,” while the karyotype and genomic topology (the physical relationship of genes within a three-dimensional nucleus) plus the gene content defines “system inheritance.” In this mini-review, the concept of karyotype or chromosomal coding will be briefly discussed, including: 1) the rationale for searching for new genomic inheritance, 2) chromosomal or karyotype coding (hypothesis, model, and its predictions), and 3) the significance and evidence of chromosomal coding (maintaining and changing the system inheritance-defined bio-systems). This mini-review aims to provide a new conceptual framework for appreciating the genome organization-based information package and its ultimate importance for future genomic and evolutionary studies.

Proposal for a simplified classification of IMD based on a pathophysiological approach: A practical guide for clinicians

In view of the rapidly expanding number of IMD discovered by next generation sequencing, we propose a simplified classification of IMD that mixes elements from a clinical diagnostic perspective and a pathophysiological approach based on three large categories. We highlight the increasing importance of complex molecule metabolism and its connection with cell biology processes. Small molecule disorders have biomarkers and are divided in two subcategories: accumulation and deficiency. Accumulation of small molecules leads to acute or progressive postnatal "intoxication", present after a symptom-free interval, aggravated by catabolism and food intake. These treatable disorders must not be missed! Deficiency of small molecules is due to impaired synthesis of compounds distal to a block or altered transport of essential molecules. This subgroup shares many clinical characteristics with complex molecule disorders. Complex molecules (like glycogen, sphingolipids, phospholipids, glycosaminoglycans, glycolipids) are poorly diffusible. Accumulation of complex molecules leads to postnatal progressive storage like in glycogen and lysosomal storage disorders. Many are treatable. Deficiency of complex molecules is related to the synthesis and recycling of these molecules, which take place in organelles. They may interfere with fœtal development. Most present as neurodevelopmental or neurodegenerative disorders unrelated to food intake. Peroxisomal disorders, CDG defects of intracellular trafficking and processing, recycling of synaptic vesicles, and tRNA synthetases also belong to this category. Only few have biomarkers and are treatable. Disorders involving primarily energy metabolism encompass defects of membrane carriers of energetic molecules as well as cytoplasmic and mitochondrial metabolic defects. This oversimplified classification is connected to the most recent available nosology of IMD.

Multi-Omics Approach: New Potential Key Mechanisms Implicated in Cardiorenal Syndromes

Cardiorenal syndromes (CRS) include a scenario of clinical interactions characterized by the heart and kidney dysfunction. The crosstalk between cardiac and renal systems is clearly evidenced but not completely understood. Multi-factorial mechanisms leading to CRS do not involve only hemodynamic parameters. In fact, in recent works on organ crosstalk endothelial injury, the alteration of normal immunologic balance, cell death, inflammatory cascades, cell adhesion molecules, cytokine and chemokine overexpression, neutrophil migration, leukocyte trafficking, caspase-mediated induction of apoptotic mechanisms and oxidative stress has been demonstrated to induce distant organ dysfunction. Furthermore, new alternative mechanisms using the multi-omics approach may be implicated in the pathogenesis of cardiorenal crosstalk. The study of “omics” modifications in the setting of cardiovascular and renal disease represents an emerging area of research. Over the last years, indeed, many studies have elucidated the exact mechanisms involved in gene expression and regulation, cellular communication and organ crosstalk. In this review, we analyze epigenetics, gene expression, small non-coding RNAs, extracellular vesicles, proteomics, and metabolomics in the setting of CRS.

P4 medicine for epilepsy and intellectual disability: nutritional therapy for inherited metabolic disease

Early identification and treatment of inherited metabolic diseases (IMDs) are essential to prevent and minimize intellectual disability (ID) and epilepsy. The oldest form of treatment, nutritional modulation, has proved beneficial for many IMDs. These conditions represent a promising model for P4 medicine - predictive, preventive, personalized, and participatory - specifically through the interpretation of individual genetic, pathophysiological, and clinical characteristics. More than 1000 IMDs have been described, and for these different nutritional modulation strategies are applied, varying from substrate reduction, supplementation of vitamins for catalyzation of enzymatic reactions or supplementation of amino acids or other nutrients, to substitution for deficient or inactivated products. This review provides an overview of all IMDs presenting with epilepsy and/or ID amenable to nutritional modulation; these are 85 in number, belonging to 27 categories. Therapeutic strategies include protein-restricted diet, ketogenic diet, fat-restricted diet, lactose-restricted diet; supplementation of amino acids, carbohydrates, or others; and supplementation of vitamins or cofactors as well as a sick-day protocol. Nutritional therapies are generally safe, affordable, and accessible, but compliance is an issue. Three different types of response exist: (1) a positive effect on seizure control and/or psychomotor development; (2) efficacy in prevention of decompensation but ongoing damage occurs; and (3) insufficient insights or evidence to establish the treatment as effective. For the latter category, we describe pyridoxine-dependent epilepsy as a case vignette for P4 medicine, discuss the benefits and challenges of nutritional modulation in IMDs, and outline novel approaches and solutions.

Knowledge about Neonatal Screening among Postpartum Women and Complexity Level of Birthing Facilities

BACKGROUND

To ascertain the degree of knowledge of postpartum women about important aspects related to the neonatal screening process and whether differences of opinion exist between those who deliver in low-complexity versus high-complexity health facilities (low-risk versus high-risk pregnancies, respectively).

METHODS

This was a prospective, cross-sectional, questionnaire-based study. The sample consisted of postpartum women recruited from 2013 to 2015 at public maternity hospitals in the city of Niterói, Brazil. Participants were divided into two groups and completed a questionnaire consisting of Likert-scored items. Continuous variables were analyzed with the Mann-Whitney test, and categorical variables, with Fisher's test. A confirmatory factor analysis of participants' answers was performed.

RESULTS

Of 188 women enrolled, 54 (28.7%) had incomplete elementary education; 119 (62.2%) had attended more than six antenatal care visits. The mean age was 25.57 years. Nearly all women (n = 179, 95.2%) were roomed-in with their infants. Knowledge of neonatal screening was very similar in the high-complexity and low-complexity groups. Divergences were limited to items regarding the risks of neonatal screening.

CONCLUSIONS

The degree of knowledge among postpartum women was similar among high- and low-complexity facilities. Those who attended high-complexity facilities had longer hospital stays and greater adherence to ethical issues regarding neonatal screening.

Substrate reduction therapy for inborn errors of metabolism

Inborn errors of metabolism (IEM) represent a growing group of monogenic disorders each associated with inherited defects in a metabolic enzyme or regulatory protein, leading to biochemical abnormalities arising from a metabolic block. Despite the well-established genetic linkage, pathophysiology and clinical manifestations for many IEMs, there remains a lack of transformative therapy. The available treatment and management options for a few IEMs are often ineffective or expensive, incurring a significant burden to individual, family, and society. The lack of IEM therapies, in large part, relates to the conceptual challenge that IEMs are loss-of-function defects arising from the defective enzyme, rendering pharmacologic rescue difficult. An emerging approach that holds promise and is the subject of a flurry of pre-/clinical applications, is substrate reduction therapy (SRT). SRT addresses a common IEM phenotype associated with toxic accumulation of substrate from the defective enzyme, by inhibiting the formation of the substrate instead of directly repairing the defective enzyme. This minireview will summarize recent highlights towards the development of emerging SRT, with focussed attention towards repurposing of currently approved drugs, approaches to validate novel targets and screen for hit molecules, as well as emerging advances in gene silencing as a therapeutic modality.

Biochemical screening of intellectually disabled and healthy children in Punjab, Pakistan: differences in liver function test and lipid profiles

Objectives: Inborn errors of metabolism (IEMs) are rare genetic disorders. Generally, IEMs are untreatable; however, some IEMs causing intellectual disability are potentially treatable if diagnosed earlier. In this study, levels of some clinically important biochemical parameters in intellectually disabled children suspected for IEMs were tested to see their association with intellectual disability, which could be helpful in preliminary screening. Methods: This comparative cross-sectional observational study was carried out from 2014 to 2017. Blood samples from 800 boys and girls (aged 4-24 years) were collected, of which 391 were healthy (IQ >90) and 409 were intellectually disabled (IQ <70) children with unknown cause. Clinically important (Liver and kidney enzymes etc.) biochemical parameters were analyzed in sera samples using commercial kits on semi-automated clinical chemistry analyzer. Results: Serum analysis showed the levels of ALP (p < 0.00001), ASAT (p = 0.001), ALAT (p = 0.016), albumin (p < 0.001), uric acid (p < 0.001), cholesterol (p < 0.001), triglycerides (p < 0.001), and hemoglobin (p = 0.005) were significantly different between healthy and intellectually disabled children. Conclusion: Changes in the liver function test and lipid profile parameters were significantly different in children with intellectual disability; however, it requires further detailed analysis for complete characterization of these diseases.

Value of genetic analysis for confirming inborn errors of metabolism detected through the Spanish neonatal screening program

The present work describes the value of genetic analysis as a confirmatory measure following the detection of suspected inborn errors of metabolism in the Spanish newborn mass spectrometry screening program. One hundred and forty-one consecutive DNA samples were analyzed by next-generation sequencing using a customized exome sequencing panel. When required, the Illumina extended clinical exome panel was used, as was Sanger sequencing or transcriptional profiling. Biochemical tests were used to confirm the results of the genetic analysis. Using the customized panel, the metabolic disease suspected in 83 newborns (59%) was confirmed. In three further cases, two monoallelic variants were detected for two genes involved in the same biochemical pathway. In the remainder, either a single variant or no variant was identified. Given the persistent absence of biochemical alterations, carrier status was assigned in 39 cases. False positives were recorded for 11. In five cases in which the biochemical pattern was persistently altered, further genetic analysis allowed the detection of two variants affecting the function of BCAT2, ACSF3, and DNAJC12, as well as a second, deep intronic variant in ETFDH or PTS. The present results suggest that genetic analysis using extended next-generation sequencing panels can be used as a confirmatory test for suspected inborn errors of metabolism detected in newborn screening programs. Biochemical tests can be very helpful when a diagnosis is unclear. In summary, simultaneous genomic and metabolomic analyses can increase the number of inborn errors of metabolism that can be confirmed following suggestive newborn screening results.

Integration of Metabolomics and Transcriptomics to Identify Gene-Metabolite Relationships Specific to Phenotype

Metabolomics plays an increasingly large role in translational research, with metabolomics data being generated in large cohorts, alongside other omics data such as gene expression. With this in mind, we provide a review of current approaches that integrate metabolomic and transcriptomic data. Furthermore, we provide a detailed framework for integrating metabolomic and transcriptomic data using a two-step approach: (1) numerical integration of gene and metabolite levels to identify phenotype (e.g., cancer)-specific gene-metabolite relationships using IntLIM and (2) knowledge-based integration, using pathway overrepresentation analysis through RaMP, a comprehensive database of biological pathways. Each step makes use of publicly available R packages ( https://github.com/mathelab/IntLIM and https://github.com/mathelab/RaMP-DB ), and provides a user-friendly web interface for analysis. These interfaces can be run locally through the package or can be accessed through our servers ( https://intlim.bmi.osumc.edu and https://ramp-db.bmi.osumc.edu ). The goal of this chapter is to provide step-by-step instructions on how to install the software and use the commands within the R framework, without the user interface (which is slower than running the commands through command line). Both packages are in continuous development so please refer to the GitHub sites to check for updates.

Metabolic Evaluation of Epilepsy: A Diagnostic Algorithm With Focus on Treatable Conditions

Although inborn errors of metabolism do not represent the most common cause of seizures, their early identification is of utmost importance, since many will require therapeutic measures beyond that of common anti-epileptic drugs, either in order to control seizures, or to decrease the risk of neurodegeneration. We translate the currently-known literature on metabolic etiologies of epilepsy (268 inborn errors of metabolism belonging to 21 categories, with 74 treatable errors), into a 2-tiered diagnostic algorithm, with the first-tier comprising accessible, affordable, and less invasive screening tests in urine and blood, with the potential to identify the majority of treatable conditions, while the second-tier tests are ordered based on individual clinical signs and symptoms. This resource aims to support the pediatrician, neurologist, biochemical, and clinical geneticists in early identification of treatable inborn errors of metabolism in a child with seizures, allowing for timely initiation of targeted therapy with the potential to improve outcomes.

Metabolomics in the clinic: A review of the shared and unique features of untargeted metabolomics for clinical research and clinical testing

Metabolomics is the untargeted measurement of the metabolome, which is composed of the complement of small molecules detected in a biological sample. As such, metabolomic analysis produces a global biochemical phenotype. It is a technology that has been utilized in the research setting for over a decade. The metabolome is directly linked to and is influenced by genetics, epigenetics, environmental factors, and the microbiome-all of which affect health. Metabolomics can be applied to human clinical diagnostics and to other fields such as veterinary medicine, nutrition, exercise, physiology, agriculture/plant biochemistry, and toxicology. Applications of metabolomics in clinical testing are emerging, but several aspects of its use as a clinical test differ from applications focused on research or biomarker discovery and need to be considered for metabolomics clinical test data to have optimum impact, be meaningful, and be used responsibly. In this review, we deconstruct aspects and challenges of metabolomics for clinical testing by illustrating the significance of test design, accurate and precise data acquisition, quality control, data processing, n-of-1 comparison to a reference population, and biochemical pathway analysis. We describe how metabolomics technology is integral to defining individual biochemical phenotypes, elaborates on human health and disease, and fits within the precision medicine landscape. Finally, we conclude by outlining some future steps needed to bring metabolomics into the clinical space and to be recognized by the broader medical and regulatory fields.

Cellular neurometabolism: a tentative to connect cell biology and metabolism in neurology

It has become increasingly evident that inborn errors of metabolism (IEMs) are particularly prevalent as diseases of the nervous system and that a broader, more inclusive definition of IEM is necessary. In fact, as long as biochemistry is involved, any kind of monogenic disease can become an IEM. This new, extended definition includes new categories and mechanisms, and as a general trend will go beyond a single biochemical pathway and/or organelle, and will appear as a connection of multiple crossroads in a system biology approach.From one side, a simplified and updated classification of IEM is presented that mixes elements from the diagnostic approach with pathophysiological considerations into three large categories based on the size of molecules ("small and simple" or "large and complex") and their implication in energy metabolism. But from another side, whatever their size, metabolites involved in IEM may behave in the brain as signalling molecules, structural components and fuels, and many metabolites have more than one role. Neurometabolism is becoming more relevant, not only in relation to these new categories of diseases but also as a necessary way to explain the mechanisms of brain damage in classically defined categories of IEM. Brain metabolism, which has been largely disregarded in the traditional approach to investigating and treating neurological diseases, is a major clue and probably the next imminent "revolution" in neurology and neuroscience. Biochemistry (metabolism) and cell neurobiology need to meet. Additionally, the brain should be studied as a system (connecting different levels of complexity).

The Implementation Process for Pharmacogenomic Testing for Cancer-Targeted Therapies

Recent advances in genomic medicine have led to the availability of genomic tests that have the potential to improve population health, yet the process for obtaining these tests and getting them reimbursed by insurers has not been described. The objective of this study was to describe the process of ordering pharmacogenomic tests by interviewing providers, patients, and laboratories about cancer-related pharmacogenomic tests. We interviewed patients who were prescribed, providers who prescribed medications that should be guided by pharmacogenomic testing, and individuals from diagnostic laboratories. A total of 10 providers, 16 patients, and eight diagnostic laboratories described logistical and insurance issues relating to ordering and receiving pharmacogenomic tests and medications. We found that the process of ordering pharmacogenomic tests is time-consuming, expensive, and complex. Ordering pharmacogenomic tests is quite different across institutions. Even in the same institution, multiple providers can order the test. Once the provider places the order for the pharmacogenomic test, the laboratory receives the request and usually begins testing without knowing how the test will be paid for. Next, the laboratory completes the pharmacogenomic testing and the results of the tests are reported to providers, patients, or placed directly in the medical record. In conclusion, processes related to ordering and obtaining insurance coverage for pharmacogenomic tests varies greatly across institutions and is time-consuming.

Precision Medicine for Neonatal Sepsis

Neonatal sepsis remains a significant cause of morbidity and mortality especially in the preterm infant population. The ability to promptly and accurately diagnose neonatal sepsis based on clinical evaluation and laboratory blood tests remains challenging. Advances in high-throughput molecular technologies have increased investigations into the utility of transcriptomic, proteomic and metabolomic approaches as diagnostic tools for neonatal sepsis. A systems-level understanding of neonatal sepsis, obtained by using omics-based technologies (at the transcriptome, proteome or metabolome level), may lead to new diagnostic tools for neonatal sepsis. In particular, recent omic-based studies have identified distinct transcriptional signatures and metabolic or proteomic biomarkers associated with sepsis. Despite the emerging need for a systems biology approach, future studies have to address the challenges of integrating multi-omic data with laboratory and clinical meta-data in order to translate outcomes into precision medicine for neonatal sepsis. Omics-based analytical approaches may advance diagnostic tools for neonatal sepsis. More research is needed to validate the recent systems biology findings in order to integrate multi-dimensional data (clinical, laboratory and multi-omic) for future translation into precision medicine for neonatal sepsis. This review will discuss the possible applications of omics-based analyses for identification of new biomarkers and diagnostic signatures for neonatal sepsis, focusing on the immune-compromised preterm infant and considerations for clinical translation.

Comparison of the serum metabolic signatures based on 1H NMR between patients and a rat model of deep vein thrombosis

Deep vein thrombosis (DVT) and pulmonary embolism (PE) have high morbidity, reduce quality of life, and can cause death. Biomarkers or genetic risk factors have not been identified in patients with DVT. In present study, serum of 61 patients suffering from DVT and a rat DVT model (n = 10) were assayed by a proton nuclear magnetic resonance (¹H NMR) metabolomics technique combing with multivariate statistical analysis to identify the metabolites. The MetPA platform was used to identify differences in the metabolic pathways between the rat model and patients. The metabolomics results discovered that 11 different metabolites in rats and 20 different metabolites in DVT patients. Seven metabolites both altered in the rats and patients. Moreover, we observed changes in the metabolic pathways, including carbohydrate metabolism, lipid metabolism, and amino acid metabolism that were induced immediately by the thrombosis. Pathway of aminoacyl-tRNA biosynthesis perturbed only in the patients which was associated with the genetic risk factor of DVT. The study demonstrated that serum ¹H NMR metabolomics can be used to diagnose DVT in the clinic. The altered pathways related to thrombosis and genetics will provide a foundation and new strategies for understanding the pathological mechanism and pharmacological targets of DVT.

Bone health in patients with inborn errors of metabolism

Inborn errors of metabolism encompass a wide spectrum of disorders, frequently affecting bone. The most important metabolic disorders that primarily influence calcium or phosphate balance, resulting in skeletal pathology, are hypophosphatemic rickets and hypophosphatasia. Conditions involving bone marrow or affecting skeletal growth and development are mainly the lysosomal storage disorders, in particular the mucopolysaccharidoses. In these disorders skeletal abnormalities are often the presenting symptom and early recognition and intervention improves outcome in many of these diseases. Many disorders of intermediary metabolism may impact bone health as well, resulting in higher frequencies of osteopenia and osteoporosis. In these conditions factors contributing to the reduced bone mineralization can be the disorder itself, the strict dietary treatment, reduced physical activity or sunlight exposure and/or early ovarian failure. Awareness of these primary or secondary bone problems amongst physicians treating patients with inborn errors of metabolism is of importance for optimization bone health and recognition of skeletal complications.